% Created 2020-09-22 mar. 09:51 % Intended LaTeX compiler: pdflatex \documentclass[conference]{IEEEtran} \usepackage[utf8]{inputenc} \usepackage[T1]{fontenc} \usepackage{graphicx} \usepackage{grffile} \usepackage{longtable} \usepackage{wrapfig} \usepackage{rotating} \usepackage[normalem]{ulem} \usepackage{amsmath} \usepackage{textcomp} \usepackage{amssymb} \usepackage{capt-of} \usepackage{hyperref} \usepackage[most]{tcolorbox} \usepackage{bm} \usepackage{booktabs} \usepackage{tabularx} \usepackage{array} \usepackage{siunitx} \IEEEoverridecommandlockouts \usepackage{cite} \usepackage{amsmath,amssymb,amsfonts} \usepackage{algorithmic} \usepackage{graphicx} \usepackage{textcomp} \usepackage{xcolor} \usepackage{cases} \usepackage{tabularx,siunitx,booktabs} \usepackage{algorithmic} \usepackage{import, hyperref} \renewcommand{\citedash}{--} \def\BibTeX{{\rm B\kern-.05em{\sc i\kern-.025em b}\kern-.08em T\kern-.1667em\lower.7ex\hbox{E}\kern-.125emX}} \usepackage{showframe} \author{\IEEEauthorblockN{Dehaeze Thomas} \IEEEauthorblockA{\textit{European Synchrotron Radiation Facility} \\ Grenoble, France\\ \textit{Precision Mechatronics Laboratory} \\ \textit{University of Liege}, Belgium \\ thomas.dehaeze@esrf.fr }\and \IEEEauthorblockN{Collette Christophe} \IEEEauthorblockA{\textit{BEAMS Department}\\ \textit{Free University of Brussels}, Belgium\\ \textit{Precision Mechatronics Laboratory} \\ \textit{University of Liege}, Belgium \\ ccollett@ulb.ac.be }} \date{2020-09-22} \title{Robust and Optimal Sensor Fusion} \begin{document} \maketitle \begin{abstract} Abstract text to be done \end{abstract} \begin{IEEEkeywords} Complementary Filters, Sensor Fusion, H-Infinity Synthesis \end{IEEEkeywords} \section{Introduction} \label{sec:org2c6d9ef} \label{sec:introduction} \section{Optimal Super Sensor Noise: \(\mathcal{H}_2\) Synthesis} \label{sec:org5aa0717} \label{sec:optimal_fusion} \subsection{Sensor Model} \label{sec:org8f1053d} \subsection{Sensor Fusion Architecture} \label{sec:orgc40deb4} \begin{figure}[htbp] \centering \includegraphics[scale=1]{figs/sensor_fusion_noise_arch.pdf} \caption{\label{fig:sensor_fusion_noise_arch}Figure caption} \end{figure} Let note \(\Phi\) the PSD. \(\tilde{n}_1\) and \(\tilde{n}_2\) are white noise with unitary power spectral density: \begin{equation} \Phi_{\tilde{n}_i}(\omega) = 1 \end{equation} \begin{equation} \hat{x} = \left( H_1 \hat{G}_1^{-1} G_1 + H_2 \hat{G}_2^{-1} G_2 \right) x + \left( H_1 \hat{G}_1^{-1} N_1 \right) \tilde{n}_1 + \left( H_2 \hat{G}_2^{-1} N_2 \right) \tilde{n}_2 \end{equation} Suppose the sensor dynamical model \(\hat{G}_i\) is perfect: \begin{equation} \hat{G}_i = G_i \end{equation} Complementary Filters \begin{equation} H_1(s) + H_2(s) = 1 \end{equation} \begin{equation} \hat{x} = x + \left( H_1 \hat{G}_1^{-1} N_1 \right) \tilde{n}_1 + \left( H_2 \hat{G}_2^{-1} N_2 \right) \tilde{n}_2 \end{equation} Perfect dynamics + filter noise \subsection{Super Sensor Noise} \label{sec:orgf4b6ca9} Let's note \(n\) the super sensor noise. Its PSD is determined by: \begin{equation} \Phi_n(\omega) = \left| H_1 \hat{G}_1^{-1} N_1 \right|^2 + \left| H_2 \hat{G}_2^{-1} N_2 \right|^2 \end{equation} \subsection{\(\mathcal{H}_2\) Synthesis of Complementary Filters} \label{sec:org5773772} The goal is to design \(H_1(s)\) and \(H_2(s)\) such that the effect of the noise sources \(\tilde{n}_1\) and \(\tilde{n}_2\) has the smallest possible effect on the noise \(n\) of the estimation \(\hat{x}\). And the goal is the minimize the Root Mean Square (RMS) value of \(n\): \begin{equation} \label{eq:rms_value_estimation} \sigma_{n} = \sqrt{\int_0^\infty \Phi_{\hat{n}}(\omega) d\omega} = \left\| \begin{matrix} \hat{G}_1^{-1} N_1 H_1 \\ \hat{G}_2^{-1} N_2 H_2 \end{matrix} \right\|_2 \end{equation} Thus, the goal is to design \(H_1(s)\) and \(H_2(s)\) such that \(H_1(s) + H_2(s) = 1\) and such that \(\left\| \begin{matrix} \hat{G}_1^{-1} N_1 H_1 \\ \hat{G}_2^{-1} N_2 H_2 \end{matrix} \right\|_2\) is minimized. \begin{equation} \begin{pmatrix} z_1 \\ z_2 \\ v \end{pmatrix} = \begin{bmatrix} \hat{G}_1^{-1} N_1 & -\hat{G}_1^{-1} N_1 \\ 0 & \hat{G}_2^{-1} N_2 \\ 1 & 0 \end{bmatrix} \begin{pmatrix} w \\ u \end{pmatrix} \end{equation} The \(\mathcal{H}_2\) synthesis of the complementary filters thus minimized the RMS value of the super sensor noise. \begin{figure}[htbp] \centering \includegraphics[scale=1]{figs/h_two_optimal_fusion.pdf} \caption{\label{fig:h_two_optimal_fusion}Figure caption} \end{figure} \subsection{Example} \label{sec:orged06a27} \subsection{Robustness Problem} \label{sec:org62b375f} \section{Robust Sensor Fusion: \(\mathcal{H}_\infty\) Synthesis} \label{sec:orgef03e7c} \label{sec:robust_fusion} \subsection{Representation of Sensor Dynamical Uncertainty} \label{sec:org9c9762b} \subsection{Sensor Fusion Architecture} \label{sec:org9572e70} \begin{equation} \hat{x} = \left( H_1 \hat{G}_1^{-1} (1 + w_1 \Delta_1) G_1 + H_2 \hat{G}_2^{-1} (1 + w_2 \Delta_2) G_2 \right) x \end{equation} with \(\Delta_i\) is any transfer function satisfying \(\| \Delta_i \|_\infty < 1\). Suppose the model inversion is equal to the nominal model: \begin{equation} \hat{G}_i = G_i \end{equation} \begin{equation} \hat{x} = \left( 1 + H_1 w_1 \Delta_1 + H_2 w_2 \Delta_2 \right) x \end{equation} \begin{figure}[htbp] \centering \includegraphics[scale=1]{figs/sensor_fusion_arch_uncertainty.pdf} \caption{\label{fig:sensor_fusion_arch_uncertainty}Figure caption} \end{figure} \subsection{Super Sensor Dynamical Uncertainty} \label{sec:orgb9ee83e} The uncertainty set of the transfer function from \(\hat{x}\) to \(x\) at frequency \(\omega\) is bounded in the complex plane by a circle centered on 1 and with a radius equal to \(|w_1(j\omega) H_1(j\omega)| + |w_2(j\omega) H_2(j\omega)|\). \begin{figure}[htbp] \centering \includegraphics[scale=1]{figs/uncertainty_set_super_sensor.pdf} \caption{\label{fig:uncertainty_set_super_sensor}Figure caption} \end{figure} \subsection{\(\mathcal{H_\infty}\) Synthesis of Complementary Filters} \label{sec:orgf4e3c8e} In order to minimize the super sensor dynamical uncertainty \begin{figure}[htbp] \centering \includegraphics[scale=1]{figs/h_infinity_robust_fusion.pdf} \caption{\label{fig:h_infinity_robust_fusion}Figure caption} \end{figure} \subsection{Example} \label{sec:org4f663bc} \section{Optimal and Robust Sensor Fusion: Mixed \(\mathcal{H}_2/\mathcal{H}_\infty\) Synthesis} \label{sec:org150b612} \label{sec:optimal_robust_fusion} \subsection{Sensor Fusion Architecture} \label{sec:org9bc69b7} \begin{figure}[htbp] \centering \includegraphics[scale=1]{figs/sensor_fusion_arch_full.pdf} \caption{\label{fig:sensor_fusion_arch_full}Figure caption} \end{figure} \subsection{Synthesis Objective} \label{sec:orgbc5ac30} \subsection{Mixed \(\mathcal{H}_2/\mathcal{H}_\infty\) Synthesis} \label{sec:org541ef02} \begin{figure}[htbp] \centering \includegraphics[scale=1]{figs/mixed_h2_hinf_synthesis.pdf} \caption{\label{fig:mixed_h2_hinf_synthesis}Figure caption} \end{figure} \subsection{Example} \label{sec:org046c2e2} \section{Experimental Validation} \label{sec:org1bb9cff} \label{sec:experimental_validation} \subsection{Experimental Setup} \label{sec:org2c63393} \subsection{Sensor Noise and Dynamical Uncertainty} \label{sec:orgb0c6496} \subsection{Mixed \(\mathcal{H}_2/\mathcal{H}_\infty\) Synthesis} \label{sec:orgfb3986f} \subsection{Super Sensor Noise and Dynamical Uncertainty} \label{sec:orgfd5c11e} \section{Conclusion} \label{sec:orgda418fa} \label{sec:conclusion} \section{Acknowledgment} \label{sec:orgabdae67} \bibliography{ref} \end{document}